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In 2024, Edge AI matured from hype to necessity. Advances in model compression, specialized hardware, and privacy regulations converged to make on-device intelligence not just possible but practical. This article explores how companies integrated edge-based learning into their workflows to improve latency, reduce costs, and strengthen data governance.
In this article we explore how organizations can move beyond experimentation and successfully deploy foundation models into production, covering architecture patterns, governance frameworks, data management strategies and monitoring practices.
In 2024, many organizations rushed to deploy generative AI and predictive systems into production. Yet few invested in ongoing oversight. Continuous model monitoring isn’t just a compliance checkbox—it’s the foundation for maintaining accuracy, fairness, and reliability as data and user behavior evolve.